Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology

Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology

This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. A distinctive feature of the proposed method is the absence of a priori parameters of the power system model. Thus, the adaptability of the dynamic s...

Full description

Bibliographic Details
Main Authors:	Mihail Senyuk, Murodbek Safaraliev, Firuz Kamalov, Hana Sulieman
Format:	Article
Language:	English
Published:	MDPI AG 2023-01-01
Series:	Mathematics
Subjects:	ensemble machine learning extreme gradient boosting power system modeling random forest transient stability
Online Access:	https://www.mdpi.com/2227-7390/11/3/525

Similar Items

Methodology for Transient Stability Enhancement of Power Systems Based on Machine Learning Algorithms and Fast Valving in a Steam Turbine
by: Mihail Senyuk, et al.
Published: (2024-05-01)

Nested ensemble selection: An effective hybrid feature selection method
by: Firuz Kamalov, et al.
Published: (2023-09-01)

A boosting ensemble learning based hybrid light gradient boosting machine and extreme gradient boosting model for predicting house prices
by: Racheal Sibindi, et al.
Published: (2023-04-01)

A System for Filling Store Displays: Pitting a Single Model against a Set of Demand Forecasting Models
by: Artur Myna, et al.
Published: (2023-02-01)

Upscaling of Latent Heat Flux in Heihe River Basin Based on Transfer Learning Model
by: Jing Lin, et al.
Published: (2023-04-01)

Crop Intensity Mapping Using Dynamic Time Warping and Machine Learning from Multi-Temporal PlanetScope Data
by: Raihan Rafif, et al.
Published: (2021-12-01)

Multi-Temporal Land Cover Change Mapping Using Google Earth Engine and Ensemble Learning Methods
by: Nimisha Wagle, et al.
Published: (2020-11-01)

Solution of the emergency control of synchronous generator modes based on the local measurements to ensure the dynamic stability
by: Mihail Senyuk, et al.
Published: (2023-01-01)

Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China
by: Wengang Zhang, et al.
Published: (2022-08-01)

Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State
by: Emmanuel Gbenga Dada, et al.
Published: (2024-09-01)

An assessment of machine learning and data balancing techniques for evaluating downgrade truck crash severity prediction in Wyoming
by: Vincent Michael Ampadu, et al.
Published: (2022-11-01)

Evaluation of the Fast Synchrophasors Estimation Algorithm Based on Physical Signals
by: Mihail Senyuk, et al.
Published: (2023-01-01)

Utilizing Machine Learning and Multi-Station Observations to Investigate the Visibility of Sea Fog in the Beibu Gulf
by: Qin Huang, et al.
Published: (2024-09-01)

Ensemble Voting Regression Based on Machine Learning for Predicting Medical Waste: A Case from Turkey
by: Babek Erdebilli, et al.
Published: (2022-07-01)

Improving Soil Thickness Estimations Based on Multiple Environmental Variables with Stacking Ensemble Methods
by: Xinchuan Li, et al.
Published: (2020-11-01)

Predicting Customer Churn using ensemble learning: Case Study of a Fixed Broadband Company
by: Arian Dhini, et al.
Published: (2021-12-01)

Prediction of Ionospheric Scintillations Using Machine Learning Techniques during Solar Cycle 24 across the Equatorial Anomaly
by: Sebwato Nasurudiin, et al.
Published: (2024-10-01)

Interpolation of GNSS Position Time Series Using GBDT, XGBoost, and RF Machine Learning Algorithms and Models Error Analysis
by: Zhen Li, et al.
Published: (2023-09-01)

Comparative Analysis of Crop Coefficient Approaches and Machine Learning Models for Predicting Water Requirements in Three Major Crops in Coastal Saline-Alkali Land
by: Shide Dong, et al.
Published: (2025-02-01)

iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction
by: Balachandran Manavalan, et al.
Published: (2018-07-01)

Deep and machine learning for daily streamflow estimation: a focus on LSTM, RFR and XGBoost
by: Özlem Terzi, et al.
Published: (2023-10-01)

Rainfall-Induced Shallow Landslide Susceptibility Mapping at Two Adjacent Catchments Using Advanced Machine Learning Algorithms
by: Ananta Man Singh Pradhan, et al.
Published: (2020-09-01)

Uncertainty Reduction in Flood Susceptibility Mapping Using Random Forest and eXtreme Gradient Boosting Algorithms in Two Tropical Desert Cities, Shibam and Marib, Yemen
by: Ali R. Al-Aizari, et al.
Published: (2024-01-01)

Tree-Based Techniques for Predicting the Compression Index of Clayey Soils
by: Tsang Long, et al.
Published: (2023-07-01)

A Cascade Ensemble Learning Model for Human Activity Recognition with Smartphones
by: Shoujiang Xu, et al.
Published: (2019-05-01)

ANALYSE THE PERFORMANCE OF ENSEMBLE CLASSIFIERS USING SAMPLING TECHNIQUES
by: M. Balamurugan, et al.
Published: (2016-07-01)

Comparison of Machine Learning Methods for Predicting Soil Total Nitrogen Content Using Landsat-8, Sentinel-1, and Sentinel-2 Images
by: Qingwen Zhang, et al.
Published: (2023-06-01)

Predicting lung cancer survivability: A machine learning regression model
by: Iffat Jabin, et al.
Published: (2021-06-01)

Predicting Hard Rock Pillar Stability Using GBDT, XGBoost, and LightGBM Algorithms
by: Weizhang Liang, et al.
Published: (2020-05-01)

A hybrid system to predict brain stroke using a combined feature selection and classifier
by: Priyanka Bathla, et al.
Published: (2024-05-01)

Prediction of Pile Bearing Capacity Using XGBoost Algorithm: Modeling and Performance Evaluation
by: Maaz Amjad, et al.
Published: (2022-02-01)

Prediction of Compressive Strength of Geopolymer Concrete Landscape Design: Application of the Novel Hybrid RF–GWO–XGBoost Algorithm
by: Jun Zhang, et al.
Published: (2024-02-01)

A Data-Driven Design for Fault Detection of Wind Turbines Using Random Forests and XGboost
by: Dahai Zhang, et al.
Published: (2018-01-01)

Comparison of Feature Selection Methods—Modelling COPD Outcomes
by: Jorge Cabral, et al.
Published: (2024-05-01)

Modeling Geospatial Distribution of Peat Layer Thickness Using Machine Learning and Aerial Laser Scanning Data
by: Janis Ivanovs, et al.
Published: (2024-04-01)

Machine learning-based prediction of mild cognitive impairment among individuals with normal cognitive function
by: Xia Wei Zhu, et al.
Published: (2024-02-01)

Power System Transient Stability Preventive Control via Aptenodytes Forsteri Optimization with an Improved Transient Stability Assessment Model
by: Zhijun Xie, et al.
Published: (2024-04-01)

Multivariate Regression Forest for Categorical Attribute Data
by: LIU Zhen-yu, SONG Xiao-ying
Published: (2022-01-01)

Analysis of Conditioning Factors in Cuenca, Ecuador, for Landslide Susceptibility Maps Generation Employing Machine Learning Methods
by: Esteban Bravo-López, et al.
Published: (2023-05-01)

Bulk Power Systems Emergency Control Based on Machine Learning Algorithms and Phasor Measurement Units Data: A State-of-the-Art Review
by: Mihail Senyuk, et al.
Published: (2024-02-01)